Evidence map›Paper›PMID 35273211›Full record

ArticleScientific reports2022

Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides.

Shan Gao, Zan Zeng, HaoNing Wang, FangYuan Chen, LiYa Huang, XiaoLong Wang

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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  15. Environmental suitability ofVeterinarni medicina · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Shan Gao *College of Wildlife & Protected Area, Ministry of Education, Northeast Forestry University, 26 Hexing Road, Xiangfang District, Harbin, 150040, Heilongjiang Province, People's Republic of China.
Zan Zeng *Department of Vascular Surgery, Changhai Hospital, Second Military Medical University, Shanghai, 200433, People's Republic of China.
HaoNing WangSchool of Geography and Tourism, Harbin University, Harbin, 150086, Heilongjiang Province, People's Republic of China.
FangYuan ChenThe Second Geomatics Cartography Institute, Ministry of Natural Resource, Harbin, 150086, Heilongjiang Province, People's Republic of China.
LiYa HuangChangbai Mountain Academy of Sciences, Antu, 133613, Jilin Province, People's Republic of China.
XiaoLong WangCollege of Wildlife & Protected Area, Ministry of Education, Northeast Forestry University, 26 Hexing Road, Xiangfang District, Harbin, 150040, Heilongjiang Province, People's Republic of China. wxlhrb123@outlook.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides. The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.

Indexed as

African Horse SicknessAfrican Horse Sickness VirusCeratopogonidaeAnimalsChinaEcosystemHorsesInsect VectorsRisk Assessment

Identifiers

PMID35273211
PMCPMC8913660

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.